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RobMixReg  

Robust Mixture Regression
View on CRAN: Click here


Download and install RobMixReg package within the R console
Install from CRAN:
install.packages("RobMixReg")

Install from Github:
library("remotes")
install_github("cran/RobMixReg")

Install by package version:
library("remotes")
install_version("RobMixReg", "1.1.0")



Attach the package and use:
library("RobMixReg")
Maintained by
Wennan Chang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-25
Latest Update: 2020-08-05
Description:
Finite mixture models are a popular technique for modelling unobserved heterogeneity or to approximate general distribution functions in a semi-parametric way. They are used in a lot of different areas such as astronomy, biology, economics, marketing or medicine. This package is the implementation of popular robust mixture regression methods based on different algorithms including: fleximix, finite mixture models and latent class regression; CTLERob, component-wise adaptive trimming likelihood estimation; mixbi, bi-square estimation; mixL, Laplacian distribution; mixt, t-distribution; TLE, trimmed likelihood estimation. The implemented algorithms includes: CTLERob stands for Component-wise adaptive Trimming Likelihood Estimation based mixture regression; mixbi stands for mixture regression based on bi-square estimation; mixLstands for mixture regression based on Laplacian distribution; TLE stands for Trimmed Likelihood Estimation based mixture regression. For more detail of the algorithms, please refer to below references. Reference: Chun Yu, Weixin Yao, Kun Chen (2017) . NeyKov N, Filzmoser P, Dimova R et al. (2007) . Bai X, Yao W. Boyer JE (2012) . Wennan Chang, Xinyu Zhou, Yong Zang, Chi Zhang, Sha Cao (2020) .
How to cite:
Wennan Chang (2020). RobMixReg: Robust Mixture Regression. R package version 1.1.0, https://cran.r-project.org/web/packages/RobMixReg. Accessed 17 Jul. 2026.
Previous versions and publish date:
(2026-07-09 08:23), 0.1.0 (2020-03-25 14:10), 0.2.0 (2020-05-11 13:10), 0.2.1 (2020-05-27 00:10), 1.0.0 (2020-06-08 11:00), 1.1.0 (2020-08-05 14:00)
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